In the educational field, reading comprehension is connected to learning achievement, and through it, one can interpret, retain, organize and value what has been read. It is an essential ability for the understanding and processing of information in learning. Furthermore, it is an essential skill to developing sustainable education. In this sense, sustainable development needs an advanced reading comprehension ability at elementary school in order to teach and learn future knowledge areas such as climate change, disaster risk reduction, biodiversity, poverty reduction, and sustainable consumption. Nevertheless, there have been few works focused on analyzing reading comprehension, particularly in Mexico, where the reference is the Programme for International Student Assessment (PISA) test on how well the Mexican students have developed this skill. Hence, this article shows the usefulness of employing Bayesian techniques in the analysis of reading comprehension at elementary school. The Bayesian network model allows for the determination of the language and communication level of achievement based on parameters such as learning style, learning pace, speed, and reading comprehension, obtaining an 85.36% precision. Moreover, the results confirm that teachers could determine changes in lesson planning and implement new pedagogical mechanisms to improve the level of learning and understanding contents.

This paper presents the case study of an SME whose main turn is the spraying and encapsulation of the Moringa oleifera leaf through the handmade production system. The SME markets the product in five presentations and produces 6200 capsules in ten hours with a total of one multifunctional operator per shift. Its supply chain is represented in four echelons: raw material preparation, manufacturing, marketing, and the final consumer. The encapsulation process of Moringa oleifera was analyzed, and the problems related to the excess inventory in the process, milligram per capsule difference, lack of standards to perform processes such as weight verification were detected. As a logistics strategy, the Demand Flow Technology methodology together with the operations diagrams and Value Stream Mapping to eliminate activities that do not add value to the product was applied. As a result, the correct assignment of tasks to workers and the increment of the production line productivity were achieved.